Research Article
Pricing-Based Partial Computation Offloading in Mobile Edge Computing
@INPROCEEDINGS{10.1007/978-3-030-41114-5_1, author={Lanhui Li and Tiejun Lv}, title={Pricing-Based Partial Computation Offloading in Mobile Edge Computing}, proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part I}, proceedings_a={CHINACOM}, year={2020}, month={2}, keywords={Mobile edge computing Partial computation offloading MEC server Pricing scheme}, doi={10.1007/978-3-030-41114-5_1} }- Lanhui Li
Tiejun Lv
Year: 2020
Pricing-Based Partial Computation Offloading in Mobile Edge Computing
CHINACOM
Springer
DOI: 10.1007/978-3-030-41114-5_1
Abstract
For mobile devices (MDs) and Internet of Things (IoT) devices with limited computing capacity and battery, offloading part of tasks to the mobile edge computing (MEC) server is attractive. In this paper, we propose a joint partial computation offloading and pricing scheme in a multi-user MEC system. Firstly, we establish MD’s cost model and MEC server’s revenue model in terms of money. Secondly, we investigate MD’s cost minimization partial offloading strategy to jointly control MD’s task allocation, local CPU frequency and the amount of computational resource blocks (CRBs) requested. Finally, we formulate the revenue maximization problem for MEC server with limited computing capacity, a heuristic algorithm is proposed for MEC server to find the optimal service price. Numerical results verify the effectiveness of our proposed scheme in cost saving and pricing.
